Well, first, let's ask some questions: - When you say "open source" repo, do you mean private repo vs public repo?
- I believe Craig as Secretary will say an SGA never hurts but isn't everything already licensed ASLv2? It's been a few weeks and a few proposals reviewed so it could be my memory. Regards, KAM -- Kevin A. McGrail VP Fundraising, Apache Software Foundation Chair Emeritus Apache SpamAssassin Project https://www.linkedin.com/in/kmcgrail - 703.798.0171 On Thu, Nov 15, 2018 at 7:27 AM hxd <hxd...@qq.com> wrote: > Currently, there are 6 repositories (IoTDB, IoTDB-JDBC, TsFile, > Spark-Connector, Hive-Connector, and Grafana-Connector) totally and we will > merge them all in one repositories. > > Only the first one is private. > > Actually we are lack of experiences about how to open source. > > Should we open all the source now or after all the Apache legal documents > are done? > > Best, > > Xiangdong Huang > > > 在 2018年11月15日，下午5:06，Willem Jiang <willem.ji...@gmail.com> 写道： > > > > Here is a question for the source code repository > > > > The main source git repo[1] is still a private repo. I think we need > > to open source the repo before sending the SGA? > > > > > > [1]https://github.com/thulab/iotdb > > > > Willem Jiang > > > > Twitter: willemjiang > > Weibo: 姜宁willem > > On Thu, Nov 15, 2018 at 4:08 PM hxd <hxd...@qq.com> wrote: > >> > >> Hi, > >> > >> In the proposal discussion process, we got 3 mentors, Justin Mclean, > Christofer Dutz, and Willem Ning Jiang. > >> > >> In the vote process, we got a new mentor, Joe Witt. > >> > >> Totally, there are one Champion and four mentors, they are: > >> > >> Kevin A. McGrail (the Champion), > >> Justin Mclean, > >> Christofer Dutz, > >> Willem Ning Jiang, and > >> Joe Witt > >> > >> I have checked their name on > http://people.apache.org/committer-index.html, and they are accurate now. > >> The name list on the proposal list ( > https://wiki.apache.org/incubator/IoTDBProposal) is also correct. > >> > >> Regards, > >> Xiangdong Huang > >> > >> > >> > >> 在 2018年11月15日，上午12:51，Kevin A. McGrail <kmcgr...@apache.org> 写道： > >> > >> Congratulations! As champion, I think the next steps are: > >> > >> 1 - Xiangdong, Can you confirm the list of mentors on the proposal is > accurate? > >> > >> 2 - Also Xiangdong, Is there anyone else that stepped forward as a > mentor during the voting process that the project wants the IPMC to approve? > >> > >> 3 - Justin, I think you have to request the creation of the podling and > then I as champion work on things like the meta data file from this page, > >> https://incubator.apache.org/policy/incubation.html, correct? > >> > >> Regards, > >> KAM > >> > >> > >> > >> > >> -- > >> Kevin A. McGrail > >> VP Fundraising, Apache Software Foundation > >> Chair Emeritus Apache SpamAssassin Project > >> https://www.linkedin.com/in/kmcgrail - 703.798.0171 > >> > >> > >> On Wed, Nov 14, 2018 at 6:29 AM hxd <hxd...@qq.com> wrote: > >>> > >>> Hi, > >>> > >>> With 8 +1 binding votes, 2 +1 non-binding votes and No +/-0 or -1 > votes, this VOTE passes. > >>> > >>> Thanks to everyone who voted! > >>> > >>> Bellow is a voting tally: > >>> > >>> Binding > >>> Von Gosling > >>> Christofer Dutz > >>> Kevin A. McGrail > >>> Felix Cheung > >>> Matt Sticker > >>> Joe Witt > >>> Justin Mclean > >>> Willem Jiang > >>> > >>> > >>> Non-binding > >>> Sheng Wu > >>> Yang Bo > >>> > >>> The vote thread: > https://lists.apache.org/thread.html/077f029ab2b52a2b19fc8d41c07438f660a8e93dd87b3895d262263c@%3Cgeneral.incubator.apache.org%3E > < > https://lists.apache.org/thread.html/077f029ab2b52a2b19fc8d41c07438f660a8e93dd87b3895d262263c@%3Cgeneral.incubator.apache.org%3E > > > >>> The proposal: https://wiki.apache.org/incubator/IoTDBProposal < > https://wiki.apache.org/incubator/IoTDBProposal> > >>> > >>> Thanks, > >>> > >>> Xiangdong Huang > >>> > >>> > >>>> 在 2018年11月7日，下午3:46，hxd <hxd...@qq.com> 写道： > >>>> > >>>> Hi, > >>>> > >>>> Sorry for the previous mail with bad format. > >>>> I'd like to call a VOTE to accept IoTDB project, a database for > managing large amounts of time series data from IoT sensors in industrial > applications, into the Apache Incubator. > >>>> The full proposal is available on the wiki: > https://wiki.apache.org/incubator/IoTDBProposal > >>>> and it is also attached below for your convenience. > >>>> > >>>> Please cast your vote: > >>>> > >>>> [ ] +1, bring IoTDB into Incubator > >>>> [ ] +0, I don't care either way, > >>>> [ ] -1, do not bring IoTDB into Incubator, because... > >>>> > >>>> The vote will open at least for 72 hours. > >>>> > >>>> Thanks, > >>>> Xiangdong Huang. > >>>> > >>>> > >>>> = IoTDB Proposal = > >>>> v0.1.1 > >>>> > >>>> > >>>> == Abstract == > >>>> IoTDB is a data store for managing large amounts of time series data > such as timestamped data from IoT sensors in industrial applications. > >>>> > >>>> == Proposal == > >>>> IoTDB is a database for managing large amount of time series data > with columnar storage, data encoding, pre-computation, and index > techniques. It has SQL-like interface to write millions of data points per > second per node and is optimized to get query results in few seconds over > trillions of data points. It can also be easily integrated with Apache > Hadoop MapReduce and Apache Spark for analytics. > >>>> > >>>> == Background == > >>>> > >>>> A new class of data management system requirements is becoming > increasingly important with the rise of the Internet of Things. There are > some database systems and technologies aimed at time series data > management. For example, Gorilla and InfluxDB which are mainly built for > data centers and monitoring application metrics. Other systems, for > example, OpenTSDB and KairosDB, are built on Apache HBase and Apache > Cassandra, respectively. > >>>> > >>>> However, many applications for time series data management have more > requirements especially in industrial applications as follows: > >>>> > >>>> * Supporting time series data which has high data frequency. For > example, a turbine engine may generate 1000 points per second (i.e., > 1000Hz), while each CPU only reports 1 data points per 5 seconds in a data > center monitoring application. > >>>> > >>>> * Supporting scanning data multi-resolutionally. For example, > aggregation operation is important for time series data. > >>>> > >>>> * Supporting special queries for time series, such as pattern > matching, time series segmentation, time-frequency transformation and > frequency query. > >>>> > >>>> * Supporting a large number of monitoring targets (i.e. time series). > An excavator may report more than 1000 time series, for example, revolving > speed of the motor-engine, the speed of the excavator, the accelerated > speed, the temperature of the water tank and so on, while a CPU or an > application monitor has much fewer time series. > >>>> > >>>> * Optimization for out-of-order data points. In the industrial > sector, it is common that equipment sends data using the UDP protocol > rather than the TCP protocol. Sometimes, the network connect is unstable > and parts of the data will be buffered for later sending. > >>>> > >>>> * Supporting long-term storage. Historical data is precious for > equipment manufacturers. Therefore, removing or unloading historical data > is highly desired for most industrial applications. The database system > must not only support fast retrieval of historical data, but also should > guarantee that the historical data does not impact the processing speed for > “hot” or current data. > >>>> > >>>> * Supporting online transaction processing (OLTP) as well as complex > analytics. It is obvious that supporting analyzing from the data files > using Apache Spark/Apache Hadoop MapReduce directly is better than > transforming data files to another file format for Big Data analytics. > >>>> > >>>> * Flexible deployment either on premise or in the cloud. IoTDB is as > simple and can be deployed on a Raspberry Pi handling hundreds of time > series. Meanwhile, the system can be also deployed in the cloud so that it > supports tens of millions ingestions per second, OLTP queries in > milliseconds, and analytics using Apache Spark/Apache Hadoop MapReduce. > >>>> > >>>> * * (1) If users deploy IoTDB on a device, such as a Raspberry Pi, a > wind turbine, or a meteorological station, the deployment of the chosen > database is designed to be simple. A device may have hundreds of time > series (but less than a thousand time series) and the database needs to > handle them. > >>>> * * (2) When deploying IoTDB in a data center, the computational > resources (i.e., the hardware configuration of servers) is not a problem > when compared to a Raspberry Pi. In this deployment, IoTDB can use more > computation resources, and has the ability to handle more time seires > (e.g., millions of time series). > >>>> > >>>> Based on these requirements, we developed IoTDB, a new data store > system for managing time series data. > >>>> > >>>> IoTDB started as a Tsinghua University research project. IoTDB's > developer community has also grown to include additional institutions, for > example, universities (e.g., Fudan University), research labs (e.g, NEL-BDS > lab), and corporations (e.g., K2Data, Tencent). Funding has been provided > by various institutions including the National Natural Science Foundation > of China, and industry sponsors, such as Lenovo and K2Data. > >>>> > >>>> == Rationale == > >>>> Because there is no existed open-sourced time series databases > covering all the above requirements, we developed IoTDB. As the system > matures, we are seeking a long-term home for the project. We believe the > Apache Software Foundation would be an ideal fit. Also joining Apache will > help coordinate and improve the development effort of the growing number of > organizations which contribute to IoTDB improving the diversity of our > community. > >>>> > >>>> IoTDB contains multiple modules, which are classified into categories: > >>>> > >>>> * '''TsFile Format''': TsFile is a new columnar file format. > >>>> * '''Adaptor for Analytics and Visualization''': Integrating TsFile > with Apache Hadoop HDFS, Apache Hadoop MapReduce and Apache Spark. Examples > of integrating IoTDB with Apache Kafka, Apache Storm and Grafana are also > provided. > >>>> * '''IoTDB Engine''': An engine which consists of SQL parser, query > plan generator, memtable, authentication and authorization,write ahead log > (WAL), crash recovery, out-of-order data handler, and index for aggregation > and pattern matching. The engine stores system data in TsFile format. > >>>> * '''IoTDB JDBC''': An implementation of Java Database Connectivity > (JDBC) for clients to connect to IoTDB using Java. > >>>> > >>>> === TsFile Format === > >>>> > >>>> TsFile format is a columnar store, which is similar with Apache > Parquet and Apache CarbonData. It has the concepts of Chunk Group, Column > Chunk, Page and Footer. Comparing with Apache Parquet and Apache > CarbonData, it is designed and optimized for time series: > >>>> > >>>> ==== Time Series Friendly Encoding ==== > >>>> IoTDB currently supports run length encoding (RLE), delta-of-delta > encoding, and Facebook's Gorilla encoding. > >>>> > >>>> Lossy encoding methods (e.g., Piecewise Linear Approximation (PLA) > and time-frequency transformation are works-in-progress. > >>>> > >>>> > >>>> ==== Chunk Group ==== > >>>> The data part of a TsFile consists of many Chunk Groups. Each Chunk > Group stores the data of a device at a time interval. A Chunk Group is > similar to the row group in Apache Parquet, while there are some > constraints of the time dimension: For each device, the time intervals of > different Chunk Groups are not overlapped and the latter Chunk Group always > has a larger timestamp. > >>>> > >>>> Given a TsFile and a query with a time range filter, the query > process can terminate scanning data once it reads data points whose > timestamp reaches the time limit of the filter. We call the feature > ''fast-return'' and it makes the time range query in a TsFile very > efficient. > >>>> > >>>> > >>>> > >>>> ==== Different Column Chunk Format (Unnecessary the Repetition (R) > and Definition (D) Fields) ==== > >>>> > >>>> While Apache Parquet and Apache CarbonData support complex data > types, e.g., nested data and sparse columns, TsFile is exclusively designed > for time series whose data model is \<device_id, series_id, timestamp, > value\>. > >>>> > >>>> In a `Chunk Group`, each time series is a `Column Chunk`. Even though > these time series belong to the same device, the data points in different > time series are not aligned in the time dimension originally. > >>>> > >>>> For example, if you have a device with 2 sensors on the same data > collection frequencies, sensor 1 may collect data at time 1521622662000 > while the other one collects data at time 1521622662001 (delta=1ms). > Therefore, each Column Chunk has its timestamps and values, which is quite > different from Apache Parquet and Apache CarbonData. Because we store the > time column along with each value column instead of making different chunks > share the same time column for the sake of diverse data frequency for > different time series, we do not store any null value on disk to align > across time series. Besides, we do not need to attach `repetition` (R) and > `definition` (D) fields on each value. Therefore, the disk space is saved > and the query latency is reduced (because we do not align data by > calculating R and D fields). > >>>> > >>>> > >>>> ==== Domain Specific Information in Each Page ==== > >>>> Similar to Apache Parquet and Apache CarbonData, a `Column Chunk` > consists of several `Pages`, and each `Page` has a `Page header`. The `Page > header` is a summary of the data in the page. > >>>> > >>>> Because TsFile is optimized for time series, the page header contains > more domain specific information, such as the minimal and maximal value, > the minimal and the maximal timestamp, the frequency and so on. TsFile can > even store the histogram of values in the page header. > >>>> > >>>> This header information helps IoTDB in speeding up queries by > skipping unnecessary pages. > >>>> > >>>> > >>>> === Adaptor for Analytics === > >>>> The TsFile provides: > >>>> > >>>> * InputFormat/OutputFormat interfaces for Reading/Writing data. > >>>> * Deep integration with Apache Spark/Hadoop MapReduce including > predicate push-down, column pruning, aggregation push down, etc. So users > can use Apache Spark SQL/HiveQL to connect and query TsFiles. > >>>> > >>>> > >>>> === IoTDB Engine === > >>>> The IoTDB engine is a database engine, which uses TsFile as its > storage file format. The IoTDB Engine supports SQL-like query plus many > useful functions: > >>>> > >>>> * Tree-based time series schema > >>>> * Log-Structured Merge (LSM)-based storage > >>>> * Overflow file for out-of-order data > >>>> * Scalable index framework > >>>> * Special queries for time series > >>>> > >>>> ==== Tree-based Time Series Schema ==== > >>>> IoTDB manages all the time series definitions using a tree structure. > A path from the root of the tree to a leaf node represents a time series. > Therefore, the unique id of a time series is a path, e.g., > `root.China.beijing.windFarm1.windTurbine1.speed`. > >>>> > >>>> This kind of schema can express `group by` naturally. For example, > `root.China.beijing.windFarm1.*.speed` represents the speed of all the wind > turbines in wind farm 1 in Beijing, China. > >>>> > >>>> ==== Log-Structured Merge (LSM)-based Storage ==== > >>>> In a time series, the data points should be ordered by their > timestamps. In IoTDB, we use Log-Structured Merge (LSM) based mechanism. > Therefore, a part of the data is stored in memory first and can be called > as `memtable`. At this time, if data points come out-of-order, we resort > them in memory. When this part of data exceeds the configured memory limit, > we flush it on disk as a `Chunk Group` into an unclosed TsFile. Finally, a > TsFile may contain several Chunk Groups, for reducing the number of small > data files, which is helpful to reduce the I/O load of the storage system > and reduces the execution time of a file-merge in LSM. Notice that the data > is time-ordered in one Chunk Group on disk, and this layout is helpful for > fast filtering in one Chunk Group for a query. > >>>> > >>>> Rule 1: In a TsFile, the Chunk Groups of one device are ordered by > timestamp (Rule 1), and it is helpful for fast filtering among Chunk Groups > for a query. > >>>> > >>>> Rule 2: When the size of the unclosed TsFile reaches the threshold > defined in the configuration file, we close the file and generate a new one > to store new arriving data spanning the entire data set. Like many systems > which use LSM-based storage, we never modify a TsFile which has been closed > except for the file-merge process (Rule 2). > >>>> > >>>> Rule 3: To reduce the number of TsFiles involved in a query process, > we guarantee that the data points in different TsFiles are not overlapping > on the time dimension after file mergence (Rule 3). > >>>> > >>>> ==== Overflow File for Out-of-order Data ==== > >>>> When a part of data is flushed on disk (and will form a `Chunk Group` > in a TsFile), the newly arriving data points whose timestamps are smaller > than the largest timestamp in the Tsfile are `out-of-order`. > >>>> > >>>> To store the out-of-order data, we organize all the troublesome > `out-of-order` data point insertions into a special TsFile, named > `UnSequenceTsFile`. In an UnSequenceTsFile, the Chunk Groups of one device > may be overlapping in the time dimension, which violates the Rule 1 and > costs additional time compared to a normal TsFile for query filtering. > >>>> > >>>> There is another special operation: updating all the data points in a > time range, e.g., `update all the speed values of device1 as 0 where the > data time is in [1521622000000, 1521622662000]`. The operation is called > when: (1) a sensor malfunctions and the database receives wrong data for a > period; (2) we may want to reset all the records. Many NoSQL time series > databases do not support such an operation. To support the operation in > IoTDB, we use a tree-based structure, Treap, to store this part of > operations and store them as `Overflow` files. > >>>> > >>>> Therefore, there are 3 kinds of data files: TsFiles, > UnSequenceTsFiles and Overflow files. TsFiles should store most of the > data. The volume of UnSequenceTsFiles depends on the workload: if there are > too many out-of-order and the time span of out-of-order is huge, the volume > will be large. Overflow files handle fewest data operations but will depend > on the use of the special operations. > >>>> > >>>> ==== LSM-tree ==== > >>>> Normally, LSM-based storage engines merge data files level by level > so that it looks like a tree structure. In this way, data is well > organized. The disadvantage is that data will be read and written several > times. If the tree has 4 levels, each data point will be rewritten at least > 4 times. > >>>> > >>>> Currently, we do not merge all the TsFiles into one because (1) the > number of TsFiles is kept lower than many LSM storage engines because a > memtable is mapped to several Chunk Groups rather than a file; (2) > different TsFiles are not overlapping with each other in the time dimension > (because of Rule 3). > >>>> > >>>> As mentioned before, TsFile supports ''fast-return'' to accelerate > queries. However, UnSequenceTsFile and Overflow files do not allow this > feature. The time spans of UnSequenceTsFile, Overflow file andTsFile may be > overlapped, which leads to more files involved in the query process. To > accelerate these queries, there is a merging process to reorganize files in > the background. All the three kinds of files: TsFiles, UnSequenceTsFiles > and Overflow files, are involved in the merging process. The merging > process is implemented using multi-threading, while each thread is > responsible for a series family. > >>>> After merging, only TsFiles are left. These files have > non-overlapping time spans and support the ''fast-return'' feature. > >>>> > >>>> ==== Scalable Index Framework ==== > >>>> We allow users to implement indexes for faster queries. We currently > support an index for pattern matching query (KV-Match index, ICDE 2019). > Another index for fast aggregation (PISA index, CIKM 2016) is a > work-in-progress. > >>>> > >>>> ==== Special Queries ==== > >>>> We currently support `group by time interval` aggregation queries and > `Fill by` operations, which are similar to those of InfluxDB. Time series > segmentation operations and frequency queries are work-in-progress. > >>>> > >>>> == Initial Goals == > >>>> The initial goals are to be open sourced and to integrate with the > Apache development process. Furthermore, we plan for incremental > development, and releases along with the Apache guidelines. > >>>> > >>>> == Current Status == > >>>> We have developed the system for more than 2 years. There are > currently 13k lines of code, some of which are generated by Antlr3 and > Thrift. There are 230 issues which have been solved and more than 1500 > commits. > >>>> > >>>> The system has been deployed in the staging environment of the State > Grid Corporation of China to handle ~3 million time series (i.e, ~30,000 > power generation assembly * ~100 sensors) and an equipment service company > in China managing ~2 million time series (i.e, ~20k devices * 100 sensors). > The insertion speed reaches ~2 million points/second/node, which is faster > than InfluxDB, OpenTSDB and Apache Cassandra in our environment. > >>>> > >>>> There are many new features in the works including those mentioned > herein. We will add more analytics functions, improve the data file merge > process, and finish the first released version of IoTDB. > >>>> > >>>> == Meritocracy == > >>>> The IoTDB project operates on meritocratic principles. Developers who > submit more code with higher quality earn more merit. We have used `Issues` > and `Pull Requests` modules on Github for collecting users' suggestions and > patches. Users who submit issues, pull requests, documents and help the > community management are welcomed and encouraged to become committers. > >>>> > >>>> == Community == > >>>> > >>>> The IoTDB project users communicate on Github ( > >>>> https://github.com/thulab/tsfile) . Developers make the > communication on a website which is similar with JIRA (Currently, only > registered users can apply to access the project for communication, url: > https://tower.im/projects/36de8571a0ff4833ae9d7f1c5c400c22/ > >>>> ). We have also introduced IoTDB at many technical conferences. Next, > we will build the mailing list for more convenience, broader communication > and archived discussions. > >>>> > >>>> If IoTDB is accepted for incubation at the Apache Software > Foundation, the primary goal is to build a larger community. We believe > that IoTDB will become a key project for time series data management, and > so, we will rely on a large community of users and developers. > >>>> > >>>> TODO: IoTDB is currently on a private Github repository ( > >>>> https://github.com/thulab/iotdb), while its subproject TsFile (a > file format for storing time series data) is open sourced on Github ( > https://github.com/thulab/tsfile > >>>> ). > >>>> > >>>> == Core Developers == > >>>> IoTDB was initially developed by 2 dozen of students and teachers at > Tsinghua University. Now, more and more developers have joined coming from > other universities: Fudan University, Northwestern Polytechnical University > and Harbin Institute of Technology in China. Other developers come from > business companies such as Lenovo and Microsoft. We will be working to > bring more and more developers into the project making contributions to > IoTDB. > >>>> > >>>> == Relationships with Other Apache Products == > >>>> IoTDB requires some Apache products (Apache Thrift, commons, > collections, httpclient). > >>>> > >>>> IoTDB-Spark-connector and IoTDB-Hadoop-connector have been developed > for supporting analysing time series data by using Apache Spark and > MapReduce. > >>>> > >>>> Overall, IoTDB is designed as an open architecture, and it can be > integrated with many other systems in the future. > >>>> > >>>> As mentioned before, in the IoTDB project, we designed a new columnar > file format, called TsFile, which is similar to Apache Parquet. However, > the new file format is optimized for time series data. > >>>> > >>>> > >>>> > >>>> == Known Risks == > >>>> > >>>> === Orphaned Products === > >>>> Given the current level of investment in IoTDB, the risk of the > project being abandoned is minimal. Time series data is more and more > important and there are several constituents who are highly inspired to > continue development. Tsinghua and NEL-BDS Lab relies on IoTDB as a > platform for a large number of long-term research projects. We have > deployed IoTDB in some company's staging environments for future > applications. > >>>> > >>>> === Inexperience with Open Source === > >>>> Students and researchers in Tsinghua University have been developing > and using open source software for a long time. It is wonderful to be > guided to join a formal open-source process for students. Some of our > committers > >>>> have experiences contributing to open source, for example: > >>>> > >>>> * druid: > >>>> > https://github.com/druid-io/druid/commit/f18cc5df97e5826c2dd8ffafba9fcb69d10a4d44 > >>>> > >>>> * druid: > >>>> > https://github.com/druid-io/druid/commit/aa7aee53ce524b7887b218333166941654788794 > >>>> > >>>> * YCSB: > >>>> https://github.com/brianfrankcooper/YCSB/pull/776 > >>>> > >>>> > >>>> Additionally, several ASF veterans and industry veterans have agreed > to mentor the project and are listed in this proposal. The project will > rely on their guidance and collective wisdom to quickly transition the > entire team of initial committers towards practicing the Apache Way. > >>>> > >>>> > >>>> === Reliance on Salaried Developers === > >>>> Most of current developers are students and researchers/professors in > universities, and their researches focus on big data management and > analytics. It is unlikely that they will change their research focus away > from big data management. We will work to ensure that the ability for the > project to continuously be stewarded and to proceed forward independent of > salaried developers is continued. > >>>> > >>>> === An Excessive Fascination with the Apache Brand === > >>>> Most of the initial developers come from Tsinghua University with no > intent to use the Apache brand for profit. We have no plans for making use > of Apache brand in press releases nor posting billboards advertising > acceptance of IoTDB into Apache Incubator. > >>>> > >>>> > >>>> == Initial Source == > >>>> IoTDB's github address and some required dependencies: > >>>> > >>>> * The storage file format: > >>>> https://github.com/thulab/tsfile > >>>> > >>>> * Adaptor for Apache Hadoop MapReduce: > >>>> https://github.com/thulab/tsfile-hadoop-connector > >>>> > >>>> * Adaptor for Apache Spark: > >>>> https://github.com/thulab/tsfile-spark-connector > >>>> > >>>> * Adaptor for Grafana: > >>>> https://github.com/thulab/iotdb-grafana > >>>> > >>>> * The database engine: > >>>> https://github.com/thulab/iotdb > >>>> (private project up to now) > >>>> * The client driver: > >>>> https://github.com/thulab/iotdb-jdbc > >>>> > >>>> > >>>> > >>>> === External Dependencies === > >>>> To the best of our knowledge, all dependencies of IoTDB are > distributed under Apache compatible licenses. Upon acceptance to the > incubator, we would begin a thorough analysis of all transitive > dependencies to verify this fact and introduce license checking into the > build and release process. > >>>> > >>>> == Documentation == > >>>> * Documentation for TsFile: > >>>> https://github.com/thulab/tsfile/wiki > >>>> > >>>> * Documentation for IoTDB and its JDBC: > >>>> http://tsfile.org/document > >>>> (Chinese only. An English version is in progress.) > >>>> > >>>> == Required Resources == > >>>> === Mailing Lists === > >>>> * > >>>> priv...@iotdb.incubator.apache.org > >>>> > >>>> * > >>>> d...@iotdb.incubator.apache.org > >>>> > >>>> * > >>>> comm...@iotdb.incubator.apache.org > >>>> > >>>> > >>>> === Git Repositories === > >>>> * > >>>> https://git-wip-us.apache.org/repos/asf/incubator-iotdb.git > >>>> > >>>> > >>>> === Issue Tracking === > >>>> * JIRA IoTDB (We currently use the issue management provided by > Github to track issues.) > >>>> > >>>> > >>>> == Initial Committers == > >>>> Tsinghua University, K2Data Company, Lenovo, Microsoft > >>>> > >>>> Jianmin Wang (jimwang at tsinghua dot edu dot cn ) > >>>> > >>>> Xiangdong Huang (sainthxd at gmail dot com) > >>>> > >>>> Jun Yuan (richard_yuan16 at 163 dot com) > >>>> > >>>> Chen Wang ( wang_chen at tsinghua dot edu dot cn) > >>>> > >>>> Jialin Qiao (qjl16 at mails dot tsinghua dot edu dot cn) > >>>> > >>>> Jinrui Zhang (jinrzhan at microsoft dot com) > >>>> > >>>> Rong Kang (kr11 at mails dot tsinghua dot edu dot cn) > >>>> > >>>> Tian Jiang（jiangtia18 at mails dot tsinghua dot edu dot cn） > >>>> > >>>> Shuo Zhang (zhangshuo at k2data dot com dot cn) > >>>> > >>>> Lei Rui (rl18 at mails dot tsinghua dot edu dot cn) > >>>> > >>>> Rui Liu (liur17 at mails dot tsinghua dot edu dot cn) > >>>> > >>>> Kun Liu (liukun16 at mails dot tsinghua dot edu dot cn) > >>>> > >>>> Gaofei Cao (cgf16 at mails dot tsinghua dot edu dot cn) > >>>> > >>>> Xinyi Zhao (xyzhao16 at mails dot tsinghua dot edu dot cn) > >>>> > >>>> Dongfang Mao (maodf17 at mails dot tsinghua dot edu dot cn) > >>>> > >>>> Tianan Li(lta18 at mails dot tsinghua dot edu dot cn) > >>>> > >>>> Yue Su (suy18 at mails dot tsinghua dot edu dot cn) > >>>> > >>>> Hui Dai (daihui_iot at lenovo dot com, yuct_iot at lenovo dot com ) > >>>> > >>>> == Sponsors == > >>>> === Champion === > >>>> Kevin A. McGrail ( > >>>> kmcgr...@apache.org > >>>> ) > >>>> > >>>> === Nominated Mentors === > >>>> Justin Mclean (justin at classsoftware dot com) > >>>> > >>>> Christofer Dutz (christofer.dutz at c-ware dot de) > >>>> > >>>> Willem Jiang (willem.jiang at gmail dot com) > >>>> > >>>> > >> > >> > > > > --------------------------------------------------------------------- > > To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org > > For additional commands, e-mail: general-h...@incubator.apache.org > > > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org > For additional commands, e-mail: general-h...@incubator.apache.org > >
